People are increasingly utilizing portable computing devices to perform various types of tasks. Accordingly, there is a desire to increase the ways in which users can interact with the devices to perform these tasks. One interaction approach that is gaining in popularity includes gesture input. To provide gesture input, a user positions himself or herself in front of a camera or sensor bar and makes a motion with a feature such as the user's hand or arm. A computing device can capture images or sensor data to attempt to recognize the motion. One problem with such analysis is that the device must not only be able to recognize the motion, but the device also must be able to recognize the feature that is to provide the motion, regardless of orientation of the feature, and separate the feature motion from other motions in the background of the images. Such an approach can be computationally expensive, particularly for portable computing devices. The computational needs can result in delayed response, hanging of the device, battery drain, or other such issues.